A smart fully mechanized coal mining working face is comprised of various heterogeneous equipment that work together in unknown coal seam environments. The goal is to form a smart operational system with comprehensive perception, decision-making, and control. This involves many work points and complex coupling relationships, indicating it needs to be performed in stages and coordinated to address key problems in all directions and along multiple points. However, there are no existing unified test or analysis tools. Therefore, this study proposed a virtual test and evaluation method for a fully mechanized mining production system with different smart levels. This is based on the concept of “real data processing–virtual scene construction–setting key information points–virtual operation and evaluation.” The actual operational data for a specific working face geology and equipment were reasonably transformed into a visual virtual scene through a movement relationship model. The virtual operations and mining conditions of the working face were accurately reproduced. Based on the sensor and execution error analyses for different smart levels, the input interface for sensing, decision-making, and control was established for each piece of equipment, and an operation evaluation system was constructed. The system comprehensively simulates and tests the key points of sensing decision-making and control with various smart levels. The experimental results showed that the virtual scene constructed based on actual operational data has a high simulation degree. Users can simulate, analyze, and evaluate the overall operations of the smart mining 2.0–4.0 working face by inputting key information. The future direction for the smart development of fully mechanized mining is highlighted.

智能综采工作面由多种异种设备组成，在未知煤层环境中协同工作。目标是形成具有综合感知、决策和控制的智能运营体系。这涉及到许多工作点和复杂的耦合关系，需要分阶段进行，协调解决各个方向和多点的关键问题。但是，没有现成的统一测试或分析工具。因此，本研究提出了一种针对不同智能程度的综采生产系统的虚拟测试与评价方法。这是基于“真实数据处理-虚拟场景构建-设置关键信息点-虚拟操作和评估”的概念。” 通过运动关系模型，将特定工作面地质和设备的实际作业数据合理转化为视觉虚拟场景。准确再现了工作面的虚拟作业和开采条件。基于不同智能级别的传感器和执行误差分析，为每台设备建立感知、决策和控制的输入接口，构建运行评价体系。系统对传感决策和控制的关键点进行了综合模拟和测试，具有不同的智能水平。实验结果表明，基于实际运行数据构建的虚拟场景具有较高的仿真度。用户可以模拟、分析和评估智能采矿 2.0-4 的整体操作。0工作面通过输入关键信息。突出了综采智能化发展的未来方向。